Replaceable Bit-based Gripper for Picking Cluttered Food Items

2026-01-01

arXiv.org

AI Summary

This study addresses the challenges of grasping and precise dispensing of cluttered, deformable food items—such as caviar and spaghetti—whose highly variable morphology and weight complicate automated handling. To this end, the authors propose a modular gripper system featuring rapidly interchangeable, task-specific end-effector bits and a belt-driven switching mechanism, integrated with a multimodal control strategy tailored for cohesive granular and entangled filamentous foods. Experimental results demonstrate that the system achieves dispensing accuracy exceeding 95% for caviar and over 80% for spaghetti by weight, significantly enhancing the automation capability and efficiency for handling diverse categories of soft, deformable food products.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Multi-modal Vision
• Machine Learning: Multimodal Learning

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG

Abstract

The food packaging industry goes through changes in food items and their weights quite rapidly. These items range from easy-to-pick, single-piece food items to flexible, long and cluttered ones. We propose a replaceable bit-based gripper system to tackle the challenge of weight-based handling of cluttered food items. The gripper features specialized food attachments(bits) that enhance its grasping capabilities, and a belt replacement system allows switching between different food items during packaging operations. It offers a wide range of control options, enabling it to grasp and drop specific weights of granular, cluttered, and entangled foods. We specifically designed bits for two flexible food items that differ in shape: ikura(salmon roe) and spaghetti. They represent the challenging categories of sticky, granular food and long, sticky, cluttered food, respectively. The gripper successfully picked up both spaghetti and ikura and demonstrated weight-specific dropping of these items with an accuracy over 80% and 95% respectively. The gripper system also exhibited quick switching between different bits, leading to the handling of a large range of food items.

Problem

• cluttered food
• weight-based handling
• flexible food items
• food packaging
• grasping

Innovation

• replaceable bit-based gripper
• food packaging automation
• weight-specific grasping
• cluttered food handling
• modular end-effector